A great advantage of CT angiography by comparison with other imaging techniques such as magnetic resonance (MR) tomography, PET (Positron Emission Tomography), SPECT (Single Photon Emission Computed Tomography) or the 3D ultrasound technique resides in that, for example, the entire vessel tree of the heart can be recorded with a single CT scan by adding a contrast agent. The 3D image data thereby obtained can be visualized using different techniques.
For a quantitative evaluation, in particular a measurement of stenoses or of plaque deposits, it is necessary for the corresponding regions of the vessel structure to be segmented from the 3D image data. This segmentation is performed in a follow-up process on an image computer.
The currently most frequently used and commercially available technique of segmentation is the technique of so-called region growing. In this technique, all the respectively adjacent pixels (voxels) are analyzed starting from seed points, which can be prescribed by the user, in the 3D image data, and identified as part of the vessel structure upon fulfillment of specific conditions. As one condition for the membership of the vessel structure, it is possible, for example, to check whether the voxel falls into a prescribed HU range (HU: Hounsfield Units).
It is also possible to prescribe for the density gradients between adjacent voxels a highest value above which the adjacent voxel is no longer regarded as part of the vessel structure. The voxels respectively newly identified as part of the vessel structure are used, in turn, as starting points for the next step of analysis or segmentation. In this way, the already identified structure grows three-dimensionally until the complete, prescribable region of the vessel structure is segmented. An example of the use of such a technique for segmenting vessel structures can be taken from the publication by T. Boskamp et al. “New Vessel Analysis Tool for Morphometric Quantification and Visualization of Vessels in CT and MR Imaging Data Sets”, Radiographics 2004, 24, 287-297, the entire contents of which are hereby incorporated herein by reference.
The known region growing technique operates in many instances satisfactorily, but does not reach all the vessels that are visible to a viewer in a display of the 3D image recording. Whereas, given a suitable 3D visualization technique, the human eye can also still detect the smallest vessels as part of the structure, the segmentation algorithm detects only specific homogeneous, coherent parts in the volume examined. Furthermore, it is also possible for the segmented structure to be washed out in adjacent image areas when they have similar HU values and lie very near to the vessel structures.